---

name: agentrelay description: Reliable agent-to-agent communication protocol for transferring large payloads via shared files with pointer references and secret code verification. Triggered by explicit 'AgentRelay:' prefix in messages. metadata: {"openclaw":{"triggerPatterns":["AgentRelay:","Please use AgentRelay skill to handle","Use AgentRelay"],"emoji":"📨"}}

AgentRelay 📨

Reliable Agent-to-Agent Communication Protocol — Solves sessions_send timeout issues for large payloads using shared files + short message pointers.

🎯 When to Use This Skill

When you see messages like the following, immediately use this Skill to handle:

Please use AgentRelay skill to handle this message:
REQ,r1_r,s/r1_r.json,,

Or

📨 AgentRelay Protocol Message

Please use AgentRelay skill to handle:
- Message Type: REQ
- Event ID: r1_r  
- File Pointer: s/r1_r.json

Key Trigger Phrases:

• "use AgentRelay skill to handle"
• "AgentRelay protocol message"
• "Use AgentRelay"

When you see these keywords, immediately execute the Commands below!

🚀 Quick Start

Standard Flow After Receiving AgentRelay Message

Step 1: Parse Message

python3 {baseDir}/run_relay.py receive "REQ,r1_r,s/r1_r.json,,"

Example output:

{
  "type": "REQ",
  "event_id": "r1_r",
  "content": {"task": "write_poem", "sender_color": "red"},
  "secret": "ABC123"
}

Step 2: Understand Task and Execute

Check the content field to understand what needs to be done (e.g., write poem, analyze data, generate report).

Step 3: Update Result

python3 {baseDir}/run_relay.py complete r1_r "Task completed" "agent:red:red"

Step 4: Send CMP Confirmation

# generate CMP message (done automatically by run_relay.py complete)
# Output: CMP,r1_r,,,ABC123
# Then send via sessions_send
sessions_send(target='agent:red:red', message='CMP,r1_r,,,ABC123')

---

📚 Commands

receive <csv_message>

Parse AgentRelay CSV message and read shared file content.

Parameters:

• csv_message: CSV format message (without AgentRelay: prefix)

Example:

python3 {baseDir}/run_relay.py receive "REQ,r1_r,s/r1_r.json,,"

Output (JSON):

{
  "type": "REQ",
  "event_id": "r1_r",
  "ptr": "s/r1_r.json",
  "content": {...},
  "secret": "ABC123"
}

---

update <event_id> <json_updates>

Update shared file content.

Parameters:

• event_id: Event ID
• json_updates: JSON format updates (merged into payload.content)

Example:

python3 {baseDir}/scripts/handle_relay.py update r1_r '{"status":"completed","result":"done"}'

Output:

{"status":"ok","file":"/path/to/r1_r.json","ptr":"s/r1_r.json"}

---

ack <event_id> <secret>

Generate ACK confirmation message.

Parameters:

• event_id: Event ID
• secret: Secret Code read from file

Example:

python3 {baseDir}/scripts/handle_relay.py ack r1_r ABC123

Output:

{
  "status": "ok",
  "ack_message": "ACK,r1_r,,,ABC123",
  "instruction": "Call sessions_send with message='ACK,r1_r,,,ABC123'"
}

---

🔄 Complete Communication Flow

Sender Agent

# 1. Prepare data
content = {
    "task": "write_poem",
    "sender": "red",
    "receiver": "orange",
    "sender_color": "red",
    "receiver_color": "orange"
}

# 2. Write to shared file
from agentrelay.api import agentrelay_send
result = agentrelay_send("orange", "REQ", "r1_r", content)

# 3. Send message with prefix
message = f"AgentRelay: {result['csv_message']}"
sessions_send(target='agent:orange:main', message=message)

Receiver Agent

# 1. Receive message: AgentRelay: REQ,r1_r,s/r1_r.json,,

# 2. Parse message
python3 {baseDir}/scripts/handle_relay.py receive "REQ,r1_r,s/r1_r.json,,"
# → Get content and secret

# 3. Understand task, call LLM to execute
# (This is your LLM capability)

# 4. Update result
python3 {baseDir}/scripts/handle_relay.py update r1_r '{"status":"completed"}'

# 5. Send ACK
ACK_OUTPUT=$(python3 {baseDir}/scripts/handle_relay.py ack r1_r SECRET)
ACK_MSG=$(echo "$ACK_OUTPUT" | jq -r '.ack_message')
sessions_send(target='agent:red:main', message="$ACK_MSG")

---

📊 Message Format Details

CSV Format

TYPE,ID,PTR,,DATA

Field Descriptions:

• TYPE: Message type (REQ | ACK | NACK | PING)
• ID: Event ID (unique identifier)
• PTR: File pointer (e.g., s/event_id.json)
• RESERVED: Reserved field (leave empty)
• DATA: Additional data (Secret Code for ACK)

Examples:

REQ,r1_r,s/r1_r.json,,          # Request
ACK,r1_r,,,ABC123               # Confirmation
NACK,r1_r,,,File not found      # Rejection
PING,test_1,,,,                 # Heartbeat test

Full Message (with prefix)

AgentRelay: REQ,r1_r,s/r1_r.json,,

Why need prefix?

• ✅ Clearly identifies this as AgentRelay protocol message
• ✅ LLM immediately knows to call AgentRelay Skill when seeing it
• ✅ Avoids confusion with other messages

---

🛡️ Security Mechanisms

1. Secret Code Verification

• Sender generates 6-character random code (e.g., ABC123)
• Secret is written to file
• Receiver must return the same Secret when ACKing
• Sender verifies Secret matches, ensuring receiver actually read the file

2. Burn-on-read (Optional)

When burn_on_read=true is set, file is automatically deleted after reading to protect sensitive data.

3. Integrity Check

File content includes SHA-256 hash to prevent tampering.

---

📁 Data Storage

• Shared Files: ~/.openclaw/data/agentrelay/storage/*.json
• Transaction Logs: ~/.openclaw/data/agentrelay/logs/transactions_*.jsonl
• Registry: ~/.openclaw/data/agentrelay/registry.json

---

🧪 Testing and Examples

Ping Test

python3 {baseDir}/scripts/ping_relay.py

5-Hop Relay Test

python3 {baseDir}/examples/relay_5hops.py

10-Hop Relay Test

python3 {baseDir}/examples/relay_10hops.py

---

❓ FAQ

Q: Why use AgentRelay instead of direct sessions_send?

A: sessions_send tends to timeout when transmitting messages larger than 30 characters. AgentRelay uses shared files + short pointers (less than 30 characters) to transmit arbitrarily large data.

Q: What is Secret Code for?

A: Secret Code is a 6-character random code used to verify the receiver actually read the file. Receiver must return the correct Secret in ACK.

Q: How long are files retained?

A: Files are retained for 24 hours by default. You can adjust this with ttl_hours parameter, or enable burn_on_read to delete immediately after reading.

---

📖 More Documentation

• README.md - Project overview
• ARCHITECTURE.md - Architecture design
• API.md - API reference
• DEPLOYMENT.md - Deployment guide

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Version: v1.0.1-alpha.3
Last Updated: 2026-02-28
Author: AgentRelay Team
Maintainer: AgentRelay Team